Temporal interpolation of groundwater level hydrographs for regional drought analysis using mixed models

Abstract Large-scale studies of the spatial and temporal variation groundwater drought status require complete inventories levels on regular time steps from many sites so that a standardised index can be calculated for each site. However, are often measured sporadically, include missing or erroneous data. A flexible efficient modelling framework is developed to fill gaps regularise data in such inventories. It uses linear mixed models account seasonal variation, long-term trends responses precipitation temperature over different scales. The only required estimate level measurements freely available gridded weather products. contribution four types at site determined thus causes interpreted. Validation reveals explain substantial proportion uncertainty predictions accurately quantified. computation takes less than 130 s requires little supervision. Hence, approach suitable upscaled represent large datasets consisting thousands boreholes.